Topic
Signature recognition
About: Signature recognition is a research topic. Over the lifetime, 2138 publications have been published within this topic receiving 37605 citations.
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TL;DR: This is the first investigation towards the use of score normalization to enhance adaptive biometric systems dealing with the change of user features over time and the experimental results show that the performance gain brought by adaptation can have a higher overall impact than scorenormalization alone.
4 citations
Patent•
25 Mar 2015
TL;DR: In this paper, an off-line handwritten signature recognition method based on non-negative matrix factorization (NMF) has been proposed, which comprises the needed steps that 1, signature data are collected, all signature images are preprocessed, and a data matrix A of all pre-processed training set signature images and B of testing set signature image needing recognizing are obtained; 2, features of the training set signatures are extracted, wherein NMF is performed on the A and a corresponding base image matrix W and a feature matrix H formed by weight vectors which are namely the
Abstract: The invention discloses an off-line handwritten signature recognition method based on non-negative matrix factorization (NMF). The method comprises the needed steps that 1, signature data are collected, all signature images are preprocessed, and a data matrix A of all preprocessed training set signature images and a data matrix B of testing set signature images needing recognizing are obtained; 2, features of the training set signature images are extracted, wherein NMF is performed on the A, and a corresponding base image matrix W and a feature matrix H formed by weight vectors which are namely the feature vectors and correspond to all the signature images are obtained; 3, features of the testing set signature images are extracted, wherein the data matrix B of the testing set signature images are projected on a base image, and a projection coefficient matrix H' is obtained; 4, training and classification decision are carried out through a support vector machine, and whether the signature is true or false is judged.
4 citations
25 Feb 2011
TL;DR: This work deals with offline verification of signature by two different algorithms and it shows promising results while dealing with random forgeries and simple forgeries; also it gives good recognition rate.
Abstract: Signature identification and verification is considered among the most popular biometric methods in the area of personal authentication. In proposed method, we deal with offline verification of signature by two different algorithms. Before extracting different features from the signature, some preprocessing of the signature is done. In preprocessing, the signature is colour normalized and scaled into a standard format. The algorithm is quite different and it deals with extraction of features based on mean, standard deviation and moment. The algorithm uses Euclidean distance classifier for comparing test signature with database. The algorithm have shown promising results while dealing with random forgeries and simple forgeries; also it gives good recognition rate.
4 citations
30 Aug 2006
TL;DR: It is found that features and correlations between features significantly influence letter identification and an algorithm based on information entropy is proposed to quantitatively evaluate the importance of letter features and the similarities between letters.
Abstract: The human vision system has high-level recognition abilities and can efficiently and accurately identify an object based on object parts. In the present study, a letter recognition experiment was designed to evaluate recognition of incomplete objects by humans. Five subjects were asked to identify partially erased English letters displayed for short time periods. We found that features and correlations between features significantly influence letter identification. An algorithm based on information entropy is proposed to quantitatively evaluate the importance of letter features and the similarities between letters.
4 citations
Proceedings Article•
01 Jan 2009
TL;DR: This paper addresses the applied problem of detecting and recognizing street name plates in urban images by a generic approach to structural object detection and recognition.
Abstract: In the paper we address the applied problem of detecting and recognizing street name plates in urban images by a generic approach to structural object detection and recognition. A structured object ...
4 citations